Blush Product Image Classification Dataset

In recent years, the retail e-commerce industry has developed rapidly. However, due to the wide variety of products, consumers often feel confused when choosing blush products, leading to low purchase decision efficiency. Existing product classification systems mainly rely on manual labeling, which is inefficient and prone to errors, unable to meet the rapidly changing market demands. This dataset aims to provide efficient and accurate image classification support for blush products, helping to improve the product recommendation system and search functionality of e-commerce platforms. The dataset contains 5000 images of blush products, taken with high-quality photographic equipment in a standardized environment to ensure image clarity and color accuracy. All data has undergone multiple rounds of labeling and consistency checks to ensure labeling accuracy and reliability. Data is stored in JPG format, organized by category for ease of subsequent analysis and use.